Unpacking educational inequality in the NT Professor Sven Silburn* & Steve Guthridge**, John McKenzie*, Lilly Li** & Shu Li** * Centre for Child Development and Education Menzies School of Health Research, Darwin, NT ** Health Gains Planning NT Department of Health, Darwin, NT

AIM How can existing data be used to enable a more integrated understanding of educational inequality in the NT?

NAPLAN Year 3 Reading (2013) 48% of NT Indigenous students had NAPLAN scores at or below the national minimum standard in 2013

Progress towards CtG targets: NAPLAN Year 3 reading at or above NMS % at or above NMS On track to meet the CtG Target by 2016 Non-Indigenous (National) Indigenous (National) Indigenous (NT) By 2018 the % of NT Indigenous children above NMS will have doubled but this will still be far below the CTG target

1. How important is the current policy focus on attendance?

Students’ attendance history: Children born in the NT (N=6,448) % of expected attendance % of expected attendance Non-Indigenous students Indigenous students

2. How much does “Place” matter in shaping attendance and achievement?

Community socio-demographic differences: % adults speaking English by % with yr 10 ed. u n

Relative influence of community factors associated with remote school attendance Mean weekly household income % Adults with year 10 education % population aged < 15 years Mean number of people per bedroom % Adults who speak English only Community remoteness (ARIA) % Population who are Indigenous % Community SES (ICSEA)

3. How do early childhood development outcomes shape subsequent school achievement?

Are AEDI outcomes associated with NAPLAN? 2012 NAPLAN Yr 3 Reading ( % < NMS) Indigenous % of children with 2009 AEDI Total Score < 25 th national %ile) Non-Indigenous R 2 linear =0.789 R 2 linear =0.032 % of children with 2009 AEDI Total Score < 25 th national %ile)

Relative influence of remote community factors predictive of 2012 NAPLAN reading < NMS Mean weekly household income Mean number of people per bedroom % Adults with year 10 education Mean school attendance % Adults who speak English only % AEDI vulnerable (2009) % population aged < 15 years

4. Do early-life health and socio-demographic factors influence NAPLAN outcomes?

Individual child factors associated with Indigenous Yr 3 reading < NMS FactorChildren N=4,603 (100%) Crude Odds Ratio Adjusted Odds Ratio Primary carer’s education <year 102,022 (43.9%) Age of mother at child’s birth <18yr718 (15.6%) Primary carers education = year 101,190 (25.8%) Male gender2,393 (51.9%) Smoking in pregnancy1,951 (42.3%) Low birth weight581 (12.6%)1.451,24 First live birth1,074 (23.3%) Gestation < 37 weeks609 (13.2%) Multivariate logistic regression: Crude and adjusted risks for NAPLAN Yr 3 Reading below the National Minimum Standard (NMS) [NT Early Child Development Data-linkage Demonstration Study: Silburn, Lynch, Guthridge & McKenzie]

Relative importance of perinatal health and socio- demographic factors for Indigenous NAPLAN Yr 3 reading Population Attributable Risk % Population Attributable Risk is the reduction in incidence if the whole population were unexposed, comparing with actual exposure pattern.

5. How can we derive a more “holistic” understanding of the key drivers of educational disadvantage?

De-identified linkage of selected data items from NT administrative datasets Datasets already linked Datasets to be linked

Summary Addressing educational inequality in the NT requires recognition that: 1.School attendance really matters 2.Levels of remoteness vary considerably 3.Community characteristics have significant influence 4.Early-life health & socio-demographic factors also matter 5.Linking child, family, community & school data will assist in identifying key causal pathways and the best leverage points for improving outcomes